Multi-objective parametric modelling during minimum quantity lubrication machining of Incoloy 800H

Abstract

This study utilizes multi-objective optimization to minimize surface roughness and maximize material removal rate (MRR) during minimum quantity lubrication (MQL) turning of Incoloy 800H under different cutting conditions. The correlations among process conditions are examined using response surface methodology (RSM) and the desirability function. The obtained optimal values for the cutting parameters are as follows: 125 m/min cutting speed, 0.1 mm/rev feed rate, and 0.05 mm depth of cut. The predicted surface roughness and MRR were 0.585 μm and 4377.932 mm3/min, respectively. A correlation coefficient of 0.9006 for surface roughness and 0.9979 for MRR indicates a significant degree of agreement between experimental data and model predictions. The results show that the application of RSM can help in identifying optimal cutting conditions and minimize the need for extensive experimental trials in machining. © Published under licence by IOP Publishing Ltd.